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Maksim231197 [3]
3 years ago
8

Does anyone know how to do this pls help

Mathematics
2 answers:
erica [24]3 years ago
7 0
Write:
x + 18 + 23 = 90

Next combine like terms (which is 18 + 23)

*Remember that combining like terms is adding or subtracting the numbers that are in one side of the equal sign (basically do not add 18, 23, and 90).

You will now get x + 41 = 90.

Now subtract 41 into 90
(90 - 41).

Your answer should be x = 49.

*Make sure this is the right answer by adding 49, 18, and 23 together. If it all equals to 90°, then the answer is correct.

irina [24]3 years ago
5 0

Answer:

49

Step-by-step explanation:

x+18+23=90 (right angle)

x+ 41=90

x=90-41

x= 49

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P(X< ) 1-P(X> ) A softball pitcher has a 0.626 probability of throwing a strike for each curve ball pitch. If the softball
Mashutka [201]

Answer:

19.49% probability that no more than 16 of them are strikes

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

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The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

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Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

n = 30, p = 0.626

So

\mu = E(X) = np = 30*0.626 = 18.78

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{30*0.626*0.374} = 2.65

What is the probability that no more than 16 of them are strikes?

Using continuity correction, this is P(X \leq 16 + 0.5) = P(X \leq 16.5), which is the pvalue of Z when X = 16.5. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{16.5 - 18.78}{2.65}

Z = -0.86

Z = -0.86 has a pvalue of 0.1949

19.49% probability that no more than 16 of them are strikes

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3 years ago
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Answer:

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